Mars United℠ Commerce is a global commerce marketing practice that aligns people, technology, and intelligence to make the business of our clients better today than it was yesterday. Our worldwide capabilities coalesce into four key disciplines — Strategy & Analytics, Content & Experiences, Digital Commerce, and Retail Consultancy — that individually deliver unmatched results for clients and collectively give them an unparalleled network of seamlessly integrated functions across the entire commerce marketing ecosystem. These disciplines are powered by our industry-leading technology platform, Marilyn®, which helps marketers understand the total business impact of their commerce marketing activation, enabling them to make better decisions, create connected experiences, and drive stronger, measurable results. Learn more at https://www.marsunited.com/.

We are seeking a Data Governance Director. Part of the Analytics Group, the Data Governance Director ensures that all retailer, vendor, and platform data used for reporting is accurate, standardized, and aligned to required schemas. This role owns data conformity, taxonomy mapping, quality control, ingestion workflows, and reporting readiness. The Director manages weekly retailer and vendor data ingestion, resolves naming inconsistencies, maintains match tables, and ensures data flows correctly into internal reporting tools. The position collaborates closely with Business Analytics, Media, Engineering, and Client Leadership to meet contractual reporting requirements and deliver a reliable single source of truth.

• Core Responsibilities: Taxonomy Governance, Data Conformity, Data Quality, Mapping and Match Tables, Data Validation, Data Entry Accuracy, Training, Reporting Readiness, Metadata Management, Documentation, Weekly Ingestion Workflow Management.
• Primary Tools: Databricks, Power BI, Excel, Looker, SQL, BigQuery

PRIMARY RESPONSIBILITIES:

As a data steward, you ensure all incoming data is accurate, compliant, and mapped to the correct taxonomy before any reporting or analytics work begins. You lead the weekly ingestion process, validate retailer and vendor files, maintain placement mapping tables, and identify gaps, mismatches, or schema alignment issues. Specifically, the Data Governance lead will:

• Own and maintain taxonomy mapping for placements, programs, budgets, and channel structures.
• Build and update match tables to align retailer and vendor naming conventions to internal schemas.
• Interpret retailer data extracts and apply standardized mapping rules required for reporting.
• Work with engineering to confirm that required fields for managed versus self service tracking are correctly populated.
• Validate all incoming files using automated and manual checks for completeness, accuracy, and consistency.
• Identify missing data, schema mismatches, and anomalies, escalating issues where needed.
• Provide training, documentation and workflow updates to drive accuracy, timeliness and alignment across teams.
• Maintain a QC coverage dashboard that highlights data gaps, unsupported fields, and connector issues and meet with key stakeholders to communicate and remediate issues.
• Maintain a list of non-compliant vendors and coordinate with internal teams or vendors to resolve structural or naming issues.
• Work with Media and Business Analytics to resolve discrepancies in spend, placements, or program level details.
• Use SQL queries, macros, and Python scripts to pull data from multiple sources and aggregate it into unified structures.
• Build automated data cleaning and transformation workflows where appropriate to support the weekly ingest cycle.
• Create summary level tables using group by logic and metric calculations to support pacing, budgeting, and performance reporting.
• Implement repeatable checks that confirm dataset completeness and alignment before reporting is refreshed.
• Maintain detailed documentation including data standards, field definitions, lineage diagrams, and transformation rules.
• Update the internal data catalog to reflect taxonomy structures, dataset attributes, mapping rules, and dependencies.
• Ensure our Data Governance policies are properly followed. 
• Prepare validated datasets for BI dashboards in Power BI and Looker.
• Validate data as it lands in platform tables and ensure mapping logic is consistent with reporting expectations.
• Support platform migrations by documenting required fields and confirming availability in new schema structures.
• Partner with Business Analytics to ensure reporting reflects accurate mapping and metric calculations.
• Coordinate with Media Activation teams to validate spend, placement, and activation level details.
• Show up, be accountable, and take responsibility for data integrity.

SKILLSETS REQUIRED:

• Bachelor’s or Master’s degree in Data Analytics, Information Systems, Computer Science, or a related field.
• Seven to ten years of experience in data governance, stewardship, analytics engineering, or data operations.
• Advanced SQL skills including joins, group by functions, aggregations, window functions, and metric calculation.
• Experience using Python to automate data cleaning, transformation, and validation tasks.
• Ability to build reusable macros and workflow scripts for repeated ingestion and QC processes.
• Experience aggregating data across multiple sources and preparing datasets for reporting.
• Familiarity with Databricks or similar data platforms.
• Working knowledge of BI tools such as Power BI or Looker.
• Solid understanding of data warehousing and lakehouse concepts including schema design and partitioning.
• Strong understanding of data governance including cataloging, metadata management, lineage, and access controls.
• Experience resolving data quality issues and managing ingestion or mapping workflows.
• Ability to interpret raw datasets and bring them into alignment with required naming and taxonomy standards.
• Experience partnering with Media, Marketing, Engineering, and Analytics teams.
• Excellent documentation skills for data dictionaries, technical specs, and workflow instructions.
• Clear communication skills for explaining data quality issues to technical and non technical audiences.